1. Field of the Invention
The present invention relates generally to a Multiple Input Multiple Output (MIMO) wireless communication system, and in particular, to an apparatus and method for generating an effective Signal to Noise Ratio (SNR) per stream for a Maximum Likelihood (ML) detection technique in the MIMO wireless communication system.
2. Description of the Related Art
With the recent increase in the demand for high-speed and high-quality data transmission, much attention is being paid to a MIMO wireless communication system using a plurality of transmit/receive antennas that is one of the technologies that may satisfy the demand. By performing a communication using a plurality of streams through a plurality of antennas, the MIMO technology can greatly improve a channel capacity compared to a single antenna. For example, a mean channel capacity increases ‘M’ times compared to a single antenna if transmit/receive ends all use transmission/receive antennas of an ‘M’ number, channels between the respective antennas are independent from each other, and the bandwidth and the whole transmission power are fixed.
In a MIMO system, various detection techniques for detecting a desired signal among signals mixed and received through a plurality of receive antennas have been proposed. Among the various detection techniques, the Maximum Likelihood (ML) detection technique has the best performance. In general, a linear scheme such as a Minimum Mean Square Error (MMSE) detection technique provides a diversity gain less than the number of receive antennas, while the ML detection technique guarantees as many diversity gains as the number of receive antennas the MIMO system has. However, because the ML detection technique is highly complicated, it is difficult to actually apply the technique despite its optimal performance.
In recent years, research for alternative techniques having performances nearly as good as the ML detection technique while reducing the operation complexity are in progress. As a result, various alternative techniques have been proposed. For example, QR decomposition-Modified Maximum Likelihood Detector (QRM-MLD), Recursive Modified Maximum Likelihood (RMML), and Sorted-RMML (S-RMML) techniques have been proposed. However, the listed techniques relate to an Open-Loop (OL) MIMO technology that does not consider how to utilize feedback information of a receive end. Similarly, the previous research does not consider how to create the feedback information. Thus, in order to apply the ML detection technique to a Close-Loop (CL) MIMO technology, there is needed an alternative for generating feedback information suitable to the ML detection technique.